Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 40 for “"Unsupervised classification"”.
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Unsupervised Classification of Music Signals: Strategies Using Timbre and Rhythm
… the ideal properties of an adaptable music classification system based on unsupervised machine learning, and argues that such a system should be based on the fundamental musical properties of timbre, rhythm, melody and harmony. The first two properties and the signal features associated with …
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UNSUPERVISED CLASSIFICATION OF HIGH-FREQUENCY OSCILLATIONS IN NEOCORTICAL EPILEPSY AND CONTROL PATIENTS
… an algorithm for the automatic detection and classification of HFOs that can be deployed without human intervention across long, continuous data records from large numbers of patients. I then use the algorithm in analyzing unique macro- and microelectrode intracranial electroencephalographic …
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Anthropogenic Influence on Blackfin Sucker (Thoburnia atripinnis) Distribution, in the Upper Barren River System, Kentucky and Tennessee
… imagine was used to create a supervised and unsupervised classification of the study area. Based on the error matrices land use/cover was classified with higher accuracy values for supervised classification over unsupervised classification. Within the study area, Barren River and Long Creek …
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Characterization of Photoacoustic Flow Cytometry Signals
… they could be manipulated to allow for further classification. Novel features were extracted from waveforms that appear to have strong classification ability. Neural networks were also used to determine classification potential and the creation of feature mapping for future unsupervised …
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Estimating farm dam storage using SPOT imagery
… resources. SPOT XS imagery and object-oriented classification was used to identify farm dams and their surface area. Two equations applied to determining the capacity of dams were used to convert surface area to volume. The results showed a similarity between fieldwork and object-oriented …
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Land Cover Change Analysis of the Mississippi Gulf Coast from 1975 to 2005 using Landsat MSS and TM Imagery
… population. Several study limitations such as unsupervised classification and misclassification are discussed to explain why a strong correlation was not found in Harrison and Jackson Counties.
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Computational topology on neural networks: from the data to the model
… as well as the problems they pose: supervised or unsupervised classification, regression... In this work, we have studied, from a computational topology point of view, two machine learning’s pillars: the datasets considered as sets of =-dimensional points, and a specific model, artificial neural …
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I-Con: A Unifying Framework for Representation Learning
… theoretical results to create state-of-the-art unsupervised image classifiers that achieve a +8% improvement over the prior state-of-the-art on unsupervised classification on ImageNet-1K. We also demonstrate that I-Con can be used to derive principled debiasing methods which improve contrastive …
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Identification of Anxiety Endophenotypes Using Multidimensional Measures of Attention
… in-lab (N = 28) or online (N = 121), we used an unsupervised clustering approach (k-means clustering) to assign individual cases to clusters, depending upon their performance on measures of attention. We used a supervised machine learning approach (random forest), to cross-validate the …
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An information base for a decision support system for management of the Mhlathuze River
… different techniques, involving supervised and unsupervised classification methods were applied to identify the land cover classes. The supervised classification method used the maximum likelihood technique, while the unsupervised classification method applied a cluster analysis technique of …
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Spectral characterization of desert surfaces in Kuwait by satellite data
… analysis was applied to the Landsat TM scene. An unsupervised classification technique produced a thematic map of the area. Data was collected on the ground at eighty sites in southeastern Kuwait. A radiometer (SE-590) was used to identify the spectral reflectance of desert surface features. A …
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Harnessing the power of intersection for data disaggregation: a novel similarity measure and unsupervised data-driven classification method applied to financial contagion
Motivated by limitations in applying existing unsupervised classification methods to economic data partitioning, a nonparametric, deterministic, and robust data-driven partitional hard cluster analysis, derived from a novel similarity measure, is introduced. The main objective of the proposed …
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Mapping the forest cover of Uganda with Spot (XS) and Landsat (ETM+) images : (a case study of Bwindi Impenetrable National Park, Uganda)
… used for the image analysis. Both supervised and unsupervised classification approaches were used. The optimal combination of bands was selected on the basis of secondary correlation analysis of the derived as well as original bands. Further identification of the best bands was based on …
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Use of ancillary data in a Landsat classification of a forested wetland
Digital Landsat cover-type classifications have often proved less accurate than hoped for, or have been less detailed than needed. Recent research efforts have used additional data to supplement the four bands of Landsat MSS data in an attempt to increase the accuracies of computer classifications. …
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Land Cover of Virginia From Landsat Thematic Mapper Imagery
… personal computers. Hypercluster aggregation, an unsupervised classification method, was used when hazy and mountainous conditions were not present. A haze correction procedure by Lavreau (1991) was used, followed by a supervised classification on coastal areas. An enhanced supervised …
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Männyn neulaskadon arviointi laserkeilauksella
… and methods used were linear regression, unsupervised classification, Maximum likelihood method, and stepwise linear regression. Field plots were divided in defoliation classes in two different ways: When divided in two classes the defoliation percentages used were 0–20 % and 20–100 % and …
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Detection of potential arable land with remote sensing and GIS. A Case Study for Kjósarhreppur
… potential arable land using both supervised and unsupervised classification. Subsequently it was examined whether it would be possible to use vegetation indices for this analysis. The resulting classification was verified by on-site analysis as well as the depth and stoniness of the potential …
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Using high resolution satellite imagery to map aquatic macropyhtes on multiple lakes in northern Indiana
… and are susceptible to invasive species. An unsupervised classification was used to develop two levels of classification. The Level I classification divided the vegetation into detailed classes of emergent and submerged vegetation based on plant structure. In the Level II classification, …
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Assessment of the environmental acceptability of refrigerants by discrete mathematics: cluster analysis and Hasse diagram technique
… with common features. Hence, a supervised and unsupervised classification was performed over 40 refrigerants. First one was a classification based upon elemental composition and functional groups present in refrigerant molecules which leads to: CFCs, HCFCs, HFCs, hydrocarbons (HCs), hydrofluoro …
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The influence of snowcover distribution and variable melt regimes on the transport of nutrients from two high Arctic watersheds
… and DIN (NH4+ and NO3-). An objective terrain classification weighted equally on slope, aspect and land surface curvature was applied to the two watersheds using an ISODATA unsupervised classification scheme to determine watershed SWE. The terrain model confirmed that topography likely explains …
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